Skip to main content
Share Your Experience: Take the 2024 Developer Survey

Questions tagged [sparse-matrix]

The tag has no usage guidance.

14 questions with no upvoted or accepted answers
Filter by
Sorted by
Tagged with
11 votes
0 answers

Complexity of finding the leading eigenvector of a graph Laplacian

Let ${\bf L}$ be the $n\times n$ Laplacian of a graph. What is the worst case complexity for calculating the maximum eigeinvector of ${\bf L}$? Are there any families of Laplacians for which it takes ...
Dimitris's user avatar
  • 1,356
8 votes
0 answers

Are there sparsifiers that approximate vertices rather than edges?

Originally introduced by Benczur and Karger, cut sparsifiers let one take a dense graph $G=(V,E)$ and produce a weighted sparse graph on the same vertex set, where - only knowing the sparse graph ...
Dana Moshkovitz's user avatar
7 votes
0 answers

What's the state of the art for matrix nuclear/trace norm optimization

I am interested in simple matrix optimizations with nuclear/trace norm: $\min_X \left(f(X) + \|X\|_*\right)$ where $\|X\|_*$ stands for the trace norm of the matrix $X$, and $f$ is a convex smooth ...
Jonathan's user avatar
7 votes
0 answers

What's new in sparse eigensystems solution

As a part of other work I need to solve relatively large (~1E5x1E5) and sparse (~100 non-zero elements in each raw in few blocks) hermitian eigensystems. Usually only few eigenvalues+vectors are ...
Misha's user avatar
  • 171
4 votes
0 answers

Precise rank of a sparse integer matrix

Consider a large sparse rectangular integer matrix. Is there a way to compute its exact rank that is better in terms of speed and/or memory usage compared to a dense matrix?
Andrei Matveiakin's user avatar
3 votes
0 answers

Cuthill - Mckee Guarantees?

I'm interested in the following problem: given $M$, a $p \times p $ symmetric sparse matrix (the number of non-zero elements in each row is at most $s \ll p$), find a matrix $B = PMP^T$ where $P$ is a ...
WeakLearner's user avatar
3 votes
0 answers

Is there an algorithm for reducing the average row width of a sparse matrix?

Suppose I have a sparse $M \times N$ matrix $A$ and I define the "width" of each row $i$ to be: $$w_i \equiv r(A_i) - l(A_i),$$ where $r(A_i)$ is the index of the rightmost nonzero element ...
Germ's user avatar
  • 191
2 votes
0 answers

computational complexity of sparse matrix powers

Given a sparse matrix $A$ with $nnz(A)$ denoting the number of non-zero entries in it. What is the computational complexity of computing $A^k$, for some positive integer $k$? As $k$ gets larger, I ...
user43464's user avatar
  • 209
1 vote
0 answers

Optimization: Turning a sparse graph of probabilities into the maximum likelihood DAG

I have a sparse matrix of probabilities that I want to turn into a DAG. If x[m,n] = pr it means that m is a descendent (direct or transitively) of n with probability pr. I want to construct a DAG over ...
Joseph Turian's user avatar
1 vote
0 answers

Stable recovery of signals by $\ell_1$ optimization

Suppose the received vector $y$ is generated from a vector $x^*$ as $y = { D}x^* + z$ for some ``dictionary" matrix ${D}$ and noise vector $z$ s.t for some $\epsilon >0$ we have, $\Vert z \Vert_2 \...
gradstudent's user avatar
  • 1,453
1 vote
0 answers

Sparse coding and matching pursuit algorithms

Is it true that all known sparse coding algorithms which work efficiently in practice don't have convergence proofs and always use an intermediate step of a matching/subspace pursuit algorithm on the ...
gradstudent's user avatar
  • 1,453
1 vote
0 answers

A well-known instance of overcomplete dictionaries

sparse representation is: A signal can be represented as a linear combination of basis functions where the set of basis functions is called dictionary and data samples are much more than their ...
B Faley's user avatar
  • 141
0 votes
0 answers

LP solver for sparse, PSD and strictly diagonally dominant matrix

I have a linear problem with a sparse, psd and strictly diagonally dominant matrix. Can you please point me to some known best solvers (in terms of runtime, or easy to be practically optimized for ...
rursw1's user avatar
  • 386
0 votes
0 answers

Sparse matrix front reducing

There is a symmetric sparse matrix with large front. This matrix is created from graph. Element with position $(i,j)$ is not zero if nodes $i$ and $j$ are connected. What algorithms can be used for ...
Pavel Oganesyan's user avatar